{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "import warnings\n",
    "\n",
    "if not sys.warnoptions:\n",
    "    warnings.simplefilter('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import tensorflow as tf\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import pandas as pd\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "from datetime import datetime\n",
    "from datetime import timedelta\n",
    "from tqdm import tqdm\n",
    "sns.set()\n",
    "tf.compat.v1.random.set_random_seed(1234)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2016-11-02</td>\n",
       "      <td>778.200012</td>\n",
       "      <td>781.650024</td>\n",
       "      <td>763.450012</td>\n",
       "      <td>768.700012</td>\n",
       "      <td>768.700012</td>\n",
       "      <td>1872400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2016-11-03</td>\n",
       "      <td>767.250000</td>\n",
       "      <td>769.950012</td>\n",
       "      <td>759.030029</td>\n",
       "      <td>762.130005</td>\n",
       "      <td>762.130005</td>\n",
       "      <td>1943200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2016-11-04</td>\n",
       "      <td>750.659973</td>\n",
       "      <td>770.359985</td>\n",
       "      <td>750.560974</td>\n",
       "      <td>762.020020</td>\n",
       "      <td>762.020020</td>\n",
       "      <td>2134800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2016-11-07</td>\n",
       "      <td>774.500000</td>\n",
       "      <td>785.190002</td>\n",
       "      <td>772.549988</td>\n",
       "      <td>782.520020</td>\n",
       "      <td>782.520020</td>\n",
       "      <td>1585100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2016-11-08</td>\n",
       "      <td>783.400024</td>\n",
       "      <td>795.632996</td>\n",
       "      <td>780.190002</td>\n",
       "      <td>790.510010</td>\n",
       "      <td>790.510010</td>\n",
       "      <td>1350800</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Date        Open        High         Low       Close   Adj Close  \\\n",
       "0  2016-11-02  778.200012  781.650024  763.450012  768.700012  768.700012   \n",
       "1  2016-11-03  767.250000  769.950012  759.030029  762.130005  762.130005   \n",
       "2  2016-11-04  750.659973  770.359985  750.560974  762.020020  762.020020   \n",
       "3  2016-11-07  774.500000  785.190002  772.549988  782.520020  782.520020   \n",
       "4  2016-11-08  783.400024  795.632996  780.190002  790.510010  790.510010   \n",
       "\n",
       "    Volume  \n",
       "0  1872400  \n",
       "1  1943200  \n",
       "2  2134800  \n",
       "3  1585100  \n",
       "4  1350800  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('../dataset/GOOG-year.csv')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    .dataframe tbody tr th {\n",
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       "      <th></th>\n",
       "      <th>0</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.112708</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.090008</td>\n",
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       "      <th>2</th>\n",
       "      <td>0.089628</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.160459</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.188066</td>\n",
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      "text/plain": [
       "          0\n",
       "0  0.112708\n",
       "1  0.090008\n",
       "2  0.089628\n",
       "3  0.160459\n",
       "4  0.188066"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "minmax = MinMaxScaler().fit(df.iloc[:, 4:5].astype('float32')) # Close index\n",
    "df_log = minmax.transform(df.iloc[:, 4:5].astype('float32')) # Close index\n",
    "df_log = pd.DataFrame(df_log)\n",
    "df_log.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Split train and test\n",
    "\n",
    "I will cut the dataset to train and test datasets,\n",
    "\n",
    "1. Train dataset derived from starting timestamp until last 30 days\n",
    "2. Test dataset derived from last 30 days until end of the dataset\n",
    "\n",
    "So we will let the model do forecasting based on last 30 days, and we will going to repeat the experiment for 10 times. You can increase it locally if you want, and tuning parameters will help you by a lot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((252, 7), (222, 1), (30, 1))"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_size = 30\n",
    "simulation_size = 10\n",
    "\n",
    "df_train = df_log.iloc[:-test_size]\n",
    "df_test = df_log.iloc[-test_size:]\n",
    "df.shape, df_train.shape, df_test.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Model:\n",
    "    def __init__(\n",
    "        self,\n",
    "        learning_rate,\n",
    "        num_layers,\n",
    "        size,\n",
    "        size_layer,\n",
    "        output_size,\n",
    "        forget_bias = 0.1,\n",
    "    ):\n",
    "        def lstm_cell(size_layer):\n",
    "            return tf.nn.rnn_cell.BasicRNNCell(size_layer)\n",
    "\n",
    "        backward_rnn_cells = tf.nn.rnn_cell.MultiRNNCell(\n",
    "            [lstm_cell(size_layer) for _ in range(num_layers)],\n",
    "            state_is_tuple = False,\n",
    "        )\n",
    "        forward_rnn_cells = tf.nn.rnn_cell.MultiRNNCell(\n",
    "            [lstm_cell(size_layer) for _ in range(num_layers)],\n",
    "            state_is_tuple = False,\n",
    "        )\n",
    "        self.X = tf.placeholder(tf.float32, (None, None, size))\n",
    "        self.Y = tf.placeholder(tf.float32, (None, output_size))\n",
    "        drop_backward = tf.contrib.rnn.DropoutWrapper(\n",
    "            backward_rnn_cells, output_keep_prob = forget_bias\n",
    "        )\n",
    "        forward_backward = tf.contrib.rnn.DropoutWrapper(\n",
    "            forward_rnn_cells, output_keep_prob = forget_bias\n",
    "        )\n",
    "        self.backward_hidden_layer = tf.placeholder(\n",
    "            tf.float32, shape = (None, num_layers * size_layer)\n",
    "        )\n",
    "        self.forward_hidden_layer = tf.placeholder(\n",
    "            tf.float32, shape = (None, num_layers * size_layer)\n",
    "        )\n",
    "        self.outputs, self.last_state = tf.nn.bidirectional_dynamic_rnn(\n",
    "            forward_backward,\n",
    "            drop_backward,\n",
    "            self.X,\n",
    "            initial_state_fw = self.forward_hidden_layer,\n",
    "            initial_state_bw = self.backward_hidden_layer,\n",
    "            dtype = tf.float32,\n",
    "        )\n",
    "        self.outputs = tf.concat(self.outputs, 2)\n",
    "        self.logits = tf.layers.dense(self.outputs[-1], output_size)\n",
    "        self.cost = tf.reduce_mean(tf.square(self.Y - self.logits))\n",
    "        self.optimizer = tf.train.AdamOptimizer(learning_rate).minimize(\n",
    "            self.cost\n",
    "        )\n",
    "        \n",
    "def calculate_accuracy(real, predict):\n",
    "    real = np.array(real) + 1\n",
    "    predict = np.array(predict) + 1\n",
    "    percentage = 1 - np.sqrt(np.mean(np.square((real - predict) / real)))\n",
    "    return percentage * 100\n",
    "\n",
    "def anchor(signal, weight):\n",
    "    buffer = []\n",
    "    last = signal[0]\n",
    "    for i in signal:\n",
    "        smoothed_val = last * weight + (1 - weight) * i\n",
    "        buffer.append(smoothed_val)\n",
    "        last = smoothed_val\n",
    "    return buffer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "num_layers = 1\n",
    "size_layer = 128\n",
    "timestamp = 5\n",
    "epoch = 300\n",
    "dropout_rate = 0.8\n",
    "future_day = test_size\n",
    "learning_rate = 0.01"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def forecast():\n",
    "    tf.reset_default_graph()\n",
    "    modelnn = Model(\n",
    "        learning_rate, num_layers, df_log.shape[1], size_layer, df_log.shape[1], dropout_rate\n",
    "    )\n",
    "    sess = tf.InteractiveSession()\n",
    "    sess.run(tf.global_variables_initializer())\n",
    "    date_ori = pd.to_datetime(df.iloc[:, 0]).tolist()\n",
    "\n",
    "    pbar = tqdm(range(epoch), desc = 'train loop')\n",
    "    for i in pbar:\n",
    "        init_value_forward = np.zeros((1, num_layers * size_layer))\n",
    "        init_value_backward = np.zeros((1, num_layers * size_layer))\n",
    "        total_loss, total_acc = [], []\n",
    "        for k in range(0, df_train.shape[0] - 1, timestamp):\n",
    "            index = min(k + timestamp, df_train.shape[0] - 1)\n",
    "            batch_x = np.expand_dims(\n",
    "                df_train.iloc[k : index, :].values, axis = 0\n",
    "            )\n",
    "            batch_y = df_train.iloc[k + 1 : index + 1, :].values\n",
    "            logits, last_state, _, loss = sess.run(\n",
    "                [modelnn.logits, modelnn.last_state, modelnn.optimizer, modelnn.cost],\n",
    "                feed_dict = {\n",
    "                    modelnn.X: batch_x,\n",
    "                    modelnn.Y: batch_y,\n",
    "                    modelnn.backward_hidden_layer: init_value_backward,\n",
    "                    modelnn.forward_hidden_layer: init_value_forward,\n",
    "                },\n",
    "            )        \n",
    "            init_value_forward = last_state[0]\n",
    "            init_value_backward = last_state[1]\n",
    "            total_loss.append(loss)\n",
    "            total_acc.append(calculate_accuracy(batch_y[:, 0], logits[:, 0]))\n",
    "        pbar.set_postfix(cost = np.mean(total_loss), acc = np.mean(total_acc))\n",
    "    \n",
    "    future_day = test_size\n",
    "\n",
    "    output_predict = np.zeros((df_train.shape[0] + future_day, df_train.shape[1]))\n",
    "    output_predict[0] = df_train.iloc[0]\n",
    "    upper_b = (df_train.shape[0] // timestamp) * timestamp\n",
    "    init_value_forward = np.zeros((1, num_layers * size_layer))\n",
    "    init_value_backward = np.zeros((1, num_layers * size_layer))\n",
    "\n",
    "    for k in range(0, (df_train.shape[0] // timestamp) * timestamp, timestamp):\n",
    "        out_logits, last_state = sess.run(\n",
    "            [modelnn.logits, modelnn.last_state],\n",
    "            feed_dict = {\n",
    "                modelnn.X: np.expand_dims(\n",
    "                    df_train.iloc[k : k + timestamp], axis = 0\n",
    "                ),\n",
    "                modelnn.backward_hidden_layer: init_value_backward,\n",
    "                modelnn.forward_hidden_layer: init_value_forward,\n",
    "            },\n",
    "        )\n",
    "        init_value_forward = last_state[0]\n",
    "        init_value_backward = last_state[1]\n",
    "        output_predict[k + 1 : k + timestamp + 1] = out_logits\n",
    "\n",
    "    if upper_b != df_train.shape[0]:\n",
    "        out_logits, last_state = sess.run(\n",
    "            [modelnn.logits, modelnn.last_state],\n",
    "            feed_dict = {\n",
    "                modelnn.X: np.expand_dims(df_train.iloc[upper_b:], axis = 0),\n",
    "                modelnn.backward_hidden_layer: init_value_backward,\n",
    "                modelnn.forward_hidden_layer: init_value_forward,\n",
    "            },\n",
    "        )\n",
    "        output_predict[upper_b + 1 : df_train.shape[0] + 1] = out_logits\n",
    "        future_day -= 1\n",
    "        date_ori.append(date_ori[-1] + timedelta(days = 1))\n",
    "\n",
    "    init_value_forward = last_state[0]\n",
    "    init_value_backward = last_state[1]\n",
    "    \n",
    "    for i in range(future_day):\n",
    "        o = output_predict[-future_day - timestamp + i:-future_day + i]\n",
    "        out_logits, last_state = sess.run(\n",
    "            [modelnn.logits, modelnn.last_state],\n",
    "            feed_dict = {\n",
    "                modelnn.X: np.expand_dims(o, axis = 0),\n",
    "                modelnn.backward_hidden_layer: init_value_backward,\n",
    "                modelnn.forward_hidden_layer: init_value_forward,\n",
    "            },\n",
    "        )\n",
    "        init_value_forward = last_state[0]\n",
    "        init_value_backward = last_state[1]\n",
    "        output_predict[-future_day + i] = out_logits[-1]\n",
    "        date_ori.append(date_ori[-1] + timedelta(days = 1))\n",
    "    \n",
    "    output_predict = minmax.inverse_transform(output_predict)\n",
    "    deep_future = anchor(output_predict[:, 0], 0.3)\n",
    "    \n",
    "    return deep_future[-test_size:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: Logging before flag parsing goes to stderr.\n",
      "W0813 00:50:36.840563 140096227489600 deprecation.py:323] From <ipython-input-6-c6fe3802893b>:12: BasicRNNCell.__init__ (from tensorflow.python.ops.rnn_cell_impl) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "This class is equivalent as tf.keras.layers.SimpleRNNCell, and will be replaced by that in Tensorflow 2.0.\n",
      "W0813 00:50:36.842919 140096227489600 deprecation.py:323] From <ipython-input-6-c6fe3802893b>:16: MultiRNNCell.__init__ (from tensorflow.python.ops.rnn_cell_impl) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "This class is equivalent as tf.keras.layers.StackedRNNCells, and will be replaced by that in Tensorflow 2.0.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "simulation 1\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "W0813 00:50:37.159364 140096227489600 lazy_loader.py:50] \n",
      "The TensorFlow contrib module will not be included in TensorFlow 2.0.\n",
      "For more information, please see:\n",
      "  * https://github.com/tensorflow/community/blob/master/rfcs/20180907-contrib-sunset.md\n",
      "  * https://github.com/tensorflow/addons\n",
      "  * https://github.com/tensorflow/io (for I/O related ops)\n",
      "If you depend on functionality not listed there, please file an issue.\n",
      "\n",
      "W0813 00:50:37.164350 140096227489600 deprecation.py:323] From <ipython-input-6-c6fe3802893b>:42: bidirectional_dynamic_rnn (from tensorflow.python.ops.rnn) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Please use `keras.layers.Bidirectional(keras.layers.RNN(cell))`, which is equivalent to this API\n",
      "W0813 00:50:37.165004 140096227489600 deprecation.py:323] From /usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/rnn.py:464: dynamic_rnn (from tensorflow.python.ops.rnn) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Please use `keras.layers.RNN(cell)`, which is equivalent to this API\n",
      "W0813 00:50:37.355312 140096227489600 deprecation.py:506] From /usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/init_ops.py:1251: calling VarianceScaling.__init__ (from tensorflow.python.ops.init_ops) with dtype is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Call initializer instance with the dtype argument instead of passing it to the constructor\n",
      "W0813 00:50:37.362000 140096227489600 deprecation.py:506] From /usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/rnn_cell_impl.py:459: calling Zeros.__init__ (from tensorflow.python.ops.init_ops) with dtype is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Call initializer instance with the dtype argument instead of passing it to the constructor\n",
      "W0813 00:50:37.520977 140096227489600 deprecation.py:323] From <ipython-input-6-c6fe3802893b>:45: dense (from tensorflow.python.layers.core) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use keras.layers.dense instead.\n",
      "train loop: 100%|██████████| 300/300 [01:04<00:00,  4.68it/s, acc=71.9, cost=0.169]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "simulation 2\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "train loop: 100%|██████████| 300/300 [01:06<00:00,  4.45it/s, acc=77.7, cost=0.11]  \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "simulation 3\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "train loop: 100%|██████████| 300/300 [01:04<00:00,  4.67it/s, acc=68.9, cost=0.211] \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "simulation 4\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "train loop: 100%|██████████| 300/300 [01:06<00:00,  4.45it/s, acc=78.9, cost=0.104] \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "simulation 5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "train loop: 100%|██████████| 300/300 [01:06<00:00,  4.53it/s, acc=70.2, cost=0.193]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "simulation 6\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "train loop: 100%|██████████| 300/300 [01:06<00:00,  4.57it/s, acc=70.6, cost=0.189]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "simulation 7\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "train loop: 100%|██████████| 300/300 [01:07<00:00,  4.43it/s, acc=66.1, cost=0.253]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "simulation 8\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "train loop: 100%|██████████| 300/300 [01:05<00:00,  4.53it/s, acc=80.6, cost=0.0892]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "simulation 9\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "train loop: 100%|██████████| 300/300 [01:07<00:00,  4.51it/s, acc=63.5, cost=0.287] \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "simulation 10\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "train loop: 100%|██████████| 300/300 [01:03<00:00,  4.71it/s, acc=72.8, cost=0.167]\n"
     ]
    }
   ],
   "source": [
    "results = []\n",
    "for i in range(simulation_size):\n",
    "    print('simulation %d'%(i + 1))\n",
    "    results.append(forecast())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "accuracies = [calculate_accuracy(df['Close'].iloc[-test_size:].values, r) for r in results]\n",
    "\n",
    "plt.figure(figsize = (15, 5))\n",
    "for no, r in enumerate(results):\n",
    "    plt.plot(r, label = 'forecast %d'%(no + 1))\n",
    "plt.plot(df['Close'].iloc[-test_size:].values, label = 'true trend', c = 'black')\n",
    "plt.legend()\n",
    "plt.title('average accuracy: %.4f'%(np.mean(accuracies)))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
